03 Jul 13 Predictive Analytics is the Future of Retail

The retail industry is under tremendous pressure to stay competitive. To do so, it has to use all the tools available, especially analytics which all retailers view as valuable and important. However, analytics maturity among retailers is low, with only a third of them conducting advanced analytics of any kind. The majority of retailers are still engaged in basic data reporting (15.6%) and basic analytics (51.9%), as illustrated in the adjacent exhibit. This can be attributed to the fact that spreadsheets are used universally in more than one-third (36%) of retail organizations. While companies need more advanced analytics, the gap between available technology and the ability to use it is increasing.
One way to counteract this effect would be to outsource the retail company’s analytics need, which currently is negligible (3%). In a majority of retail companies (71%), each department is responsible for its own analytics resources, or the companies’ IT department is primarily responsible for analytics (53%). However, cooperation between people who have the experience with the sophisticated tools needed to design and deploy analytics and the business department is low. This lack of a stellar working relationship renders the analytics useless as accurate and timely data becomes suspect.

Growth of predictive models in retail analyticsPredictive analytics technology can provide retailers glimpses of what may happen, the consequences of actions and scenarios for how to respond to change. Many retail businesses could use predictive analytics to manage inventory more effectively by getting a read on sales trends sooner, limiting stock-outs and dealing with slow-moving items earlier in a season. Yet predictive analytics are not yet high-priority analytics capabilities for most retailers. Exceptions are back-end retail processes, such as supply chain (16%) and merchandizing (14%), as depicted in the exhibit below.

As of today, the retail giants – Wal-Mart, Target, and Amazon – are the leaders in predictive retail analytics, though they all use different methods to infer insights:

In-house departmental expertise: Amazon has an analytics team for each business division. Though these teams share their findings with each other, the company has a core team that focuses purely on “Big Data”.

Establishing captive centers: Target has leveraged its operations in India to develop its system for customer analytics giving it the competitive advantage of knowing its customers better than any other retailer. Its most famous success story is when its analytics team discovered a teenager was pregnant before her father.

These above options are expensive, and retailers without the necessary budgets should consider outsourcing their predictive analytics process to companies which have the expertise. Outsourcing also offers the advantage of integrating data between departments within the organization, and external data sources, such as Alexa web traffic information to deliver more insights about customers.

Developing predictive analytics expertise across various business functions in the retail industry, from the age-old customer management to the new-era social media is unfeasible for all except the large retail giants. The advent of big data in retail is another factor to consider as storage, analysis, and insights require a dedicated company-wide analytics team. Analytics service providers with a proven track record of domain expertise in predictive algorithms/models will the clear winners in the retail analytics race in the long run.